/* SPDX-License-Identifier: GPL-2.0-or-later */ /* * Copyright (C) 2019, Google Inc. * * geometry.cpp - Geometry classes tests */ #include #include #include "test.h" using namespace std; using namespace libcamera; class GeometryTest : public Test { protected: bool compare(const Size &lhs, const Size &rhs, bool (*op)(const Size &lhs, const Size &rhs), const char *opName, bool expect) { bool result = op(lhs, rhs); if (result != expect) { cout << "Size(" << lhs.width << ", " << lhs.height << ") " << opName << " " << "Size(" << rhs.width << ", " << rhs.height << ") " << "test failed" << std::endl; return false; } return true; } int run() { if (!Size().isNull() || !Size(0, 0).isNull()) { cout << "Null size incorrectly reported as not null" << endl; return TestFail; } if (Size(0, 100).isNull() || Size(100, 0).isNull() || Size(100, 100).isNull()) { cout << "Non-null size incorrectly reported as null" << endl; return TestFail; } /* Test alignDownTo(), alignUpTo(), boundTo() and expandTo() */ Size s(50, 50); s.alignDownTo(16, 16); if (s != Size(48, 48)) { cout << "Size::alignDownTo() test failed" << endl; return TestFail; } s.alignUpTo(32, 32); if (s != Size(64, 64)) { cout << "Size::alignUpTo() test failed" << endl; return TestFail; } s.boundTo({ 40, 40 }); if (s != Size(40, 40)) { cout << "Size::boundTo() test failed" << endl; return TestFail; } s.expandTo({ 50, 50 }); if (s != Size(50, 50)) { cout << "Size::expandTo() test failed" << endl; return TestFail; } s.alignDownTo(16, 16).alignUpTo(32, 32) .boundTo({ 40, 80 }).expandTo({ 16, 80 }); if (s != Size(40, 80)) { cout << "Size chained in-place modifiers test failed" << endl; return TestFail; } /* Test alignedDownTo(), alignedUpTo(), boundedTo() and expandedTo() */ if (Size(0, 0).alignedDownTo(16, 8) != Size(0, 0) || Size(1, 1).alignedDownTo(16, 8) != Size(0, 0) || Size(16, 8).alignedDownTo(16, 8) != Size(16, 8)) { cout << "Size::alignedDownTo() test failed" << endl; return TestFail; } if (Size(0, 0).alignedUpTo(16, 8) != Size(0, 0) || Size(1, 1).alignedUpTo(16, 8) != Size(16, 8) || Size(16, 8).alignedUpTo(16, 8) != Size(16, 8)) { cout << "Size::alignedUpTo() test failed" << endl; return TestFail; } if (Size(0, 0).boundedTo({ 100, 100 }) != Size(0, 0) || Size(200, 50).boundedTo({ 100, 100 }) != Size(100, 50) || Size(50, 200).boundedTo({ 100, 100 }) != Size(50, 100)) { cout << "Size::boundedTo() test failed" << endl; return TestFail; } if (Size(0, 0).expandedTo({ 100, 100 }) != Size(100, 100) || Size(200, 50).expandedTo({ 100, 100 }) != Size(200, 100) || Size(50, 200).expandedTo({ 100, 100 }) != Size(100, 200)) { cout << "Size::expandedTo() test failed" << endl; return TestFail; } /* Test Size equality and inequality. */ if (!compare(Size(100, 100), Size(100, 100), &operator==, "==", true)) return TestFail; if (!compare(Size(100, 100), Size(100, 100), &operator!=, "!=", false)) return TestFail; if (!compare(Size(100, 100), Size(200, 100), &operator==, "==", false)) return TestFail; if (!compare(Size(100, 100), Size(200, 100), &operator!=, "!=", true)) return TestFail; if (!compare(Size(100, 100), Size(100, 200), &operator==, "==", false)) return TestFail; if (!compare(Size(100, 100), Size(100, 200), &operator!=, "!=", true)) return TestFail; /* Test Size ordering based on combined with and height. */ if (!compare(Size(100, 100), Size(200, 200), &operator<, "<", true)) return TestFail; if (!compare(Size(100, 100), Size(200, 200), &operator<=, "<=", true)) return TestFail; if (!compare(Size(100, 100), Size(200, 200), &operator>, ">", false)) return TestFail; if (!compare(Size(100, 100), Size(200, 200), &operator>=, ">=", false)) return TestFail; if (!compare(Size(200, 200), Size(100, 100), &operator<, "<", false)) return TestFail; if (!compare(Size(200, 200), Size(100, 100), &operator<=, "<=", false)) return TestFail; if (!compare(Size(200, 200), Size(100, 100), &operator>, ">", true)) return TestFail; if (!compare(Size(200, 200), Size(100, 100), &operator>=, ">=", true)) return TestFail; /* Test Size ordering based on area (with overlapping sizes). */ if (!compare(Size(200, 100), Size(100, 400), &operator<, "<", true)) return TestFail; if (!compare(Size(200, 100), Size(100, 400), &operator<=, "<=", true)) return TestFail; if (!compare(Size(200, 100), Size(100, 400), &operator>, ">", false)) return TestFail; if (!compare(Size(200, 100), Size(100, 400), &operator>=, ">=", false)) return TestFail; if (!compare(Size(100, 400), Size(200, 100), &operator<, "<", false)) return TestFail; if (!compare(Size(100, 400), Size(200, 100), &operator<=, "<=", false)) return TestFail; if (!compare(Size(100, 400), Size(200, 100), &operator>, ">", true)) return TestFail; if (!compare(Size(100, 400), Size(200, 100), &operator>=, ">=", true)) return TestFail; /* Test Size ordering based on width (with identical areas). */ if (!compare(Size(100, 200), Size(200, 100), &operator<, "<", true)) return TestFail; if (!compare(Size(100, 200), Size(200, 100), &operator<=, "<=", true)) return TestFail; if (!compare(Size(100, 200), Size(200, 100), &operator>, ">", false)) return TestFail; if (!compare(Size(100, 200), Size(200, 100), &operator>=, ">=", false)) return TestFail; if (!compare(Size(200, 100), Size(100, 200), &operator<, "<", false)) return TestFail; if (!compare(Size(200, 100), Size(100, 200), &operator<=, "<=", false)) return TestFail; if (!compare(Size(200, 100), Size(100, 200), &operator>, ">", true)) return TestFail; if (!compare(Size(200, 100), Size(100, 200), &operator>=, ">=", true)) return TestFail; /* Test Rectangle::isNull(). */ if (!Rectangle(0, 0, 0, 0).isNull() || !Rectangle(1, 1, 0, 0).isNull()) { cout << "Null rectangle incorrectly reported as not null" << endl; return TestFail; } if (Rectangle(0, 0, 0, 1).isNull() || Rectangle(0, 0, 1, 0).isNull() || Rectangle(0, 0, 1, 1).isNull()) { cout << "Non-null rectangle incorrectly reported as null" << endl; return TestFail; } return TestPass; } }; TEST_REGISTER(GeometryTest) f='#n100'>100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867

/* SPDX-License-Identifier: BSD-2-Clause */
/*
 * Copyright (C) 2019, Raspberry Pi Ltd
 *
 * ALSC (auto lens shading correction) control algorithm
 */

#include <algorithm>
#include <functional>
#include <math.h>
#include <numeric>

#include <libcamera/base/log.h>
#include <libcamera/base/span.h>

#include "../awb_status.h"
#include "alsc.h"

/* Raspberry Pi ALSC (Auto Lens Shading Correction) algorithm. */

using namespace RPiController;
using namespace libcamera;

LOG_DEFINE_CATEGORY(RPiAlsc)

#define NAME "rpi.alsc"

static const double InsufficientData = -1.0;

Alsc::Alsc(Controller *controller)
	: Algorithm(controller)
{
	asyncAbort_ = asyncStart_ = asyncStarted_ = asyncFinished_ = false;
	asyncThread_ = std::thread(std::bind(&Alsc::asyncFunc, this));
}

Alsc::~Alsc()
{
	{
		std::lock_guard<std::mutex> lock(mutex_);
		asyncAbort_ = true;
	}
	asyncSignal_.notify_one();
	asyncThread_.join();
}

char const *Alsc::name() const
{
	return NAME;
}

static int generateLut(Array2D<double> &lut, const libcamera::YamlObject &params)
{
	/* These must be signed ints for the co-ordinate calculations below. */
	int X = lut.dimensions().width, Y = lut.dimensions().height;
	double cstrength = params["corner_strength"].get<double>(2.0);
	if (cstrength <= 1.0) {
		LOG(RPiAlsc, Error) << "corner_strength must be > 1.0";
		return -EINVAL;
	}

	double asymmetry = params["asymmetry"].get<double>(1.0);
	if (asymmetry < 0) {
		LOG(RPiAlsc, Error) << "asymmetry must be >= 0";
		return -EINVAL;
	}

	double f1 = cstrength - 1, f2 = 1 + sqrt(cstrength);
	double R2 = X * Y / 4 * (1 + asymmetry * asymmetry);
	int num = 0;
	for (int y = 0; y < Y; y++) {
		for (int x = 0; x < X; x++) {
			double dy = y - Y / 2 + 0.5,
			       dx = (x - X / 2 + 0.5) * asymmetry;
			double r2 = (dx * dx + dy * dy) / R2;
			lut[num++] =
				(f1 * r2 + f2) * (f1 * r2 + f2) /
				(f2 * f2); /* this reproduces the cos^4 rule */
		}
	}
	return 0;
}

static int readLut(Array2D<double> &lut, const libcamera::YamlObject &params)
{
	if (params.size() != lut.size()) {
		LOG(RPiAlsc, Error) << "Invalid number of entries in LSC table";
		return -EINVAL;
	}

	int num = 0;
	for (const auto &p : params.asList()) {
		auto value = p.get<double>();
		if (!value)
			return -EINVAL;
		lut[num++] = *value;
	}

	return 0;
}

static int readCalibrations(std::vector<AlscCalibration> &calibrations,
			    const libcamera::YamlObject &params,
			    std::string const &name, const Size &size)
{
	if (params.contains(name)) {
		double lastCt = 0;
		for (const auto &p : params[name].asList()) {
			auto value = p["ct"].get<double>();
			if (!value)
				return -EINVAL;
			double ct = *value;
			if (ct <= lastCt) {
				LOG(RPiAlsc, Error)
					<< "Entries in " << name << " must be in increasing ct order";
				return -EINVAL;
			}
			AlscCalibration calibration;
			calibration.ct = lastCt = ct;

			const libcamera::YamlObject &table = p["table"];
			if (table.size() != size.width * size.height) {
				LOG(RPiAlsc, Error)
					<< "Incorrect number of values for ct "
					<< ct << " in " << name;
				return -EINVAL;
			}

			int num = 0;
			calibration.table.resize(size);
			for (const auto &elem : table.asList()) {
				value = elem.get<double>();
				if (!value)
					return -EINVAL;
				calibration.table[num++] = *value;
			}

			calibrations.push_back(std::move(calibration));
			LOG(RPiAlsc, Debug)
				<< "Read " << name << " calibration for ct " << ct;
		}
	}
	return 0;
}

int Alsc::read(const libcamera::YamlObject &params)
{
	config_.tableSize = getHardwareConfig().awbRegions;
	config_.framePeriod = params["frame_period"].get<uint16_t>(12);
	config_.startupFrames = params["startup_frames"].get<uint16_t>(10);
	config_.speed = params["speed"].get<double>(0.05);
	double sigma = params["sigma"].get<double>(0.01);
	config_.sigmaCr = params["sigma_Cr"].get<double>(sigma);
	config_.sigmaCb = params["sigma_Cb"].get<double>(sigma);
	config_.minCount = params["min_count"].get<double>(10.0);
	config_.minG = params["min_G"].get<uint16_t>(50);
	config_.omega = params["omega"].get<double>(1.3);
	config_.nIter = params["n_iter"].get<uint32_t>(config_.tableSize.width + config_.tableSize.height);
	config_.luminanceStrength =
		params["luminance_strength"].get<double>(1.0);

	config_.luminanceLut.resize(config_.tableSize, 1.0);
	int ret = 0;

	if (params.contains("corner_strength"))
		ret = generateLut(config_.luminanceLut, params);
	else if (params.contains("luminance_lut"))
		ret = readLut(config_.luminanceLut, params["luminance_lut"]);
	else
		LOG(RPiAlsc, Warning)
			<< "no luminance table - assume unity everywhere";
	if (ret)
		return ret;

	ret = readCalibrations(config_.calibrationsCr, params, "calibrations_Cr",
			       config_.tableSize);
	if (ret)
		return ret;
	ret = readCalibrations(config_.calibrationsCb, params, "calibrations_Cb",
			       config_.tableSize);
	if (ret)
		return ret;

	config_.defaultCt = params["default_ct"].get<double>(4500.0);
	config_.threshold = params["threshold"].get<double>(1e-3);
	config_.lambdaBound = params["lambda_bound"].get<double>(0.05);

	return 0;
}

static double getCt(Metadata *metadata, double defaultCt);
static void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
			Array2D<double> &calTable);
static void resampleCalTable(const Array2D<double> &calTableIn, CameraMode const &cameraMode,
			     Array2D<double> &calTableOut);
static void compensateLambdasForCal(const Array2D<double> &calTable,
				    const Array2D<double> &oldLambdas,
				    Array2D<double> &newLambdas);
static void addLuminanceToTables(std::array<Array2D<double>, 3> &results,
				 const Array2D<double> &lambdaR, double lambdaG,
				 const Array2D<double> &lambdaB,
				 const Array2D<double> &luminanceLut,
				 double luminanceStrength);

void Alsc::initialise()
{
	frameCount2_ = frameCount_ = framePhase_ = 0;
	firstTime_ = true;
	ct_ = config_.defaultCt;

	const size_t XY = config_.tableSize.width * config_.tableSize.height;

	for (auto &r : syncResults_)
		r.resize(config_.tableSize);
	for (auto &r : prevSyncResults_)
		r.resize(config_.tableSize);
	for (auto &r : asyncResults_)
		r.resize(config_.tableSize);

	luminanceTable_.resize(config_.tableSize);
	asyncLambdaR_.resize(config_.tableSize);
	asyncLambdaB_.resize(config_.tableSize);
	/* The lambdas are initialised in the SwitchMode. */
	lambdaR_.resize(config_.tableSize);
	lambdaB_.resize(config_.tableSize);

	/* Temporaries for the computations, but sensible to allocate this up-front! */
	for (auto &c : tmpC_)
		c.resize(config_.tableSize);
	for (auto &m : tmpM_)
		m.resize(XY);
}

void Alsc::waitForAysncThread()
{
	if (asyncStarted_) {
		asyncStarted_ = false;
		std::unique_lock<std::mutex> lock(mutex_);
		syncSignal_.wait(lock, [&] {
			return asyncFinished_;
		});
		asyncFinished_ = false;
	}
}

static bool compareModes(CameraMode const &cm0, CameraMode const &cm1)
{
	/*
	 * Return true if the modes crop from the sensor significantly differently,
	 * or if the user transform has changed.
	 */
	if (cm0.transform != cm1.transform)
		return true;
	int leftDiff = abs(cm0.cropX - cm1.cropX);
	int topDiff = abs(cm0.cropY - cm1.cropY);
	int rightDiff = fabs(cm0.cropX + cm0.scaleX * cm0.width -
			     cm1.cropX - cm1.scaleX * cm1.width);
	int bottomDiff = fabs(cm0.cropY + cm0.scaleY * cm0.height -
			      cm1.cropY - cm1.scaleY * cm1.height);
	/*
	 * These thresholds are a rather arbitrary amount chosen to trigger
	 * when carrying on with the previously calculated tables might be
	 * worse than regenerating them (but without the adaptive algorithm).
	 */
	int thresholdX = cm0.sensorWidth >> 4;
	int thresholdY = cm0.sensorHeight >> 4;
	return leftDiff > thresholdX || rightDiff > thresholdX ||
	       topDiff > thresholdY || bottomDiff > thresholdY;
}

void Alsc::switchMode(CameraMode const &cameraMode,
		      [[maybe_unused]] Metadata *metadata)
{
	/*
	 * We're going to start over with the tables if there's any "significant"
	 * change.
	 */
	bool resetTables = firstTime_ || compareModes(cameraMode_, cameraMode);

	/* Believe the colour temperature from the AWB, if there is one. */
	ct_ = getCt(metadata, ct_);

	/* Ensure the other thread isn't running while we do this. */
	waitForAysncThread();

	cameraMode_ = cameraMode;

	/*
	 * We must resample the luminance table like we do the others, but it's
	 * fixed so we can simply do it up front here.
	 */
	resampleCalTable(config_.luminanceLut, cameraMode_, luminanceTable_);

	if (resetTables) {
		/*
		 * Upon every "table reset", arrange for something sensible to be
		 * generated. Construct the tables for the previous recorded colour
		 * temperature. In order to start over from scratch we initialise
		 * the lambdas, but the rest of this code then echoes the code in
		 * doAlsc, without the adaptive algorithm.
		 */
		std::fill(lambdaR_.begin(), lambdaR_.end(), 1.0);
		std::fill(lambdaB_.begin(), lambdaB_.end(), 1.0);
		Array2D<double> &calTableR = tmpC_[0], &calTableB = tmpC_[1], &calTableTmp = tmpC_[2];
		getCalTable(ct_, config_.calibrationsCr, calTableTmp);
		resampleCalTable(calTableTmp, cameraMode_, calTableR);
		getCalTable(ct_, config_.calibrationsCb, calTableTmp);
		resampleCalTable(calTableTmp, cameraMode_, calTableB);
		compensateLambdasForCal(calTableR, lambdaR_, asyncLambdaR_);
		compensateLambdasForCal(calTableB, lambdaB_, asyncLambdaB_);
		addLuminanceToTables(syncResults_, asyncLambdaR_, 1.0, asyncLambdaB_,
				     luminanceTable_, config_.luminanceStrength);
		prevSyncResults_ = syncResults_;
		framePhase_ = config_.framePeriod; /* run the algo again asap */
		firstTime_ = false;
	}
}

void Alsc::fetchAsyncResults()
{
	LOG(RPiAlsc, Debug) << "Fetch ALSC results";
	asyncFinished_ = false;
	asyncStarted_ = false;
	syncResults_ = asyncResults_;
}

double getCt(Metadata *metadata, double defaultCt)
{
	AwbStatus awbStatus;
	awbStatus.temperatureK = defaultCt; /* in case nothing found */
	if (metadata->get("awb.status", awbStatus) != 0)
		LOG(RPiAlsc, Debug) << "no AWB results found, using "
				    << awbStatus.temperatureK;
	else
		LOG(RPiAlsc, Debug) << "AWB results found, using "
				    << awbStatus.temperatureK;
	return awbStatus.temperatureK;
}

static void copyStats(RgbyRegions &regions, StatisticsPtr &stats,
		      std::array<Array2D<double>, 3> &prevSyncResults)
{
	if (!regions.numRegions())
		regions.init(stats->awbRegions.size());

	const std::vector<double> &rTable = prevSyncResults[0].data(); //status.r;
	const std::vector<double> &gTable = prevSyncResults[1].data(); //status.g;
	const std::vector<double> &bTable = prevSyncResults[2].data(); //status.b;
	for (unsigned int i = 0; i < stats->awbRegions.numRegions(); i++) {
		auto r = stats->awbRegions.get(i);
		if (stats->colourStatsPos == Statistics::ColourStatsPos::PostLsc) {
			r.val.rSum = static_cast<uint64_t>(r.val.rSum / rTable[i]);
			r.val.gSum = static_cast<uint64_t>(r.val.gSum / gTable[i]);
			r.val.bSum = static_cast<uint64_t>(r.val.bSum / bTable[i]);
		}
		regions.set(i, r);
	}
}

void Alsc::restartAsync(StatisticsPtr &stats, Metadata *imageMetadata)
{
	LOG(RPiAlsc, Debug) << "Starting ALSC calculation";
	/*
	 * Get the current colour temperature. It's all we need from the
	 * metadata. Default to the last CT value (which could be the default).
	 */
	ct_ = getCt(imageMetadata, ct_);
	/*
	 * We have to copy the statistics here, dividing out our best guess of
	 * the LSC table that the pipeline applied to them which we get from
	 * prevSyncResults_.
	 */
	copyStats(statistics_, stats, prevSyncResults_);
	framePhase_ = 0;
	asyncStarted_ = true;
	{
		std::lock_guard<std::mutex> lock(mutex_);
		asyncStart_ = true;
	}
	asyncSignal_.notify_one();
}

void Alsc::prepare(Metadata *imageMetadata)
{
	/*
	 * Count frames since we started, and since we last poked the async
	 * thread.
	 */
	if (frameCount_ < (int)config_.startupFrames)
		frameCount_++;
	double speed = frameCount_ < (int)config_.startupFrames
			       ? 1.0
			       : config_.speed;
	LOG(RPiAlsc, Debug)
		<< "frame count " << frameCount_ << " speed " << speed;
	{
		std::unique_lock<std::mutex> lock(mutex_);
		if (asyncStarted_ && asyncFinished_)
			fetchAsyncResults();
	}
	/* Apply IIR filter to results and program into the pipeline. */
	for (unsigned int j = 0; j < syncResults_.size(); j++) {
		for (unsigned int i = 0; i < syncResults_[j].size(); i++)
			prevSyncResults_[j][i] = speed * syncResults_[j][i] + (1.0 - speed) * prevSyncResults_[j][i];
	}
	/* Put output values into status metadata. */
	AlscStatus status;
	status.r = prevSyncResults_[0].data();
	status.g = prevSyncResults_[1].data();
	status.b = prevSyncResults_[2].data();
	imageMetadata->set("alsc.status", status);
	/*
	 * Put the results in the global metadata as well. This will be used by
	 * AWB to factor in the colour shading correction.
	 */
	getGlobalMetadata().set("alsc.status", status);
}

void Alsc::process(StatisticsPtr &stats, Metadata *imageMetadata)
{
	/*
	 * Count frames since we started, and since we last poked the async
	 * thread.
	 */
	if (framePhase_ < (int)config_.framePeriod)
		framePhase_++;
	if (frameCount2_ < (int)config_.startupFrames)
		frameCount2_++;
	LOG(RPiAlsc, Debug) << "frame_phase " << framePhase_;
	if (framePhase_ >= (int)config_.framePeriod ||
	    frameCount2_ < (int)config_.startupFrames) {
		if (asyncStarted_ == false)
			restartAsync(stats, imageMetadata);
	}
}

void Alsc::asyncFunc()
{
	while (true) {
		{
			std::unique_lock<std::mutex> lock(mutex_);
			asyncSignal_.wait(lock, [&] {
				return asyncStart_ || asyncAbort_;
			});
			asyncStart_ = false;
			if (asyncAbort_)
				break;
		}
		doAlsc();
		{
			std::lock_guard<std::mutex> lock(mutex_);
			asyncFinished_ = true;
		}
		syncSignal_.notify_one();
	}
}

void getCalTable(double ct, std::vector<AlscCalibration> const &calibrations,
		 Array2D<double> &calTable)
{
	if (calibrations.empty()) {
		std::fill(calTable.begin(), calTable.end(), 1.0);
		LOG(RPiAlsc, Debug) << "no calibrations found";
	} else if (ct <= calibrations.front().ct) {
		calTable = calibrations.front().table;
		LOG(RPiAlsc, Debug) << "using calibration for "
				    << calibrations.front().ct;
	} else if (ct >= calibrations.back().ct) {
		calTable = calibrations.back().table;
		LOG(RPiAlsc, Debug) << "using calibration for "
				    << calibrations.back().ct;
	} else {
		int idx = 0;
		while (ct > calibrations[idx + 1].ct)
			idx++;
		double ct0 = calibrations[idx].ct, ct1 = calibrations[idx + 1].ct;
		LOG(RPiAlsc, Debug)
			<< "ct is " << ct << ", interpolating between "
			<< ct0 << " and " << ct1;
		for (unsigned int i = 0; i < calTable.size(); i++)
			calTable[i] =
				(calibrations[idx].table[i] * (ct1 - ct) +
				 calibrations[idx + 1].table[i] * (ct - ct0)) /
				(ct1 - ct0);
	}
}

void resampleCalTable(const Array2D<double> &calTableIn,
		      CameraMode const &cameraMode,
		      Array2D<double> &calTableOut)
{
	int X = calTableIn.dimensions().width;
	int Y = calTableIn.dimensions().height;

	/*
	 * Precalculate and cache the x sampling locations and phases to save
	 * recomputing them on every row.
	 */
	int xLo[X], xHi[X];
	double xf[X];
	double scaleX = cameraMode.sensorWidth /
			(cameraMode.width * cameraMode.scaleX);
	double xOff = cameraMode.cropX / (double)cameraMode.sensorWidth;
	double x = .5 / scaleX + xOff * X - .5;
	double xInc = 1 / scaleX;
	for (int i = 0; i < X; i++, x += xInc) {
		xLo[i] = floor(x);
		xf[i] = x - xLo[i];
		xHi[i] = std::min(xLo[i] + 1, X - 1);
		xLo[i] = std::max(xLo[i], 0);
		if (!!(cameraMode.transform & libcamera::Transform::HFlip)) {
			xLo[i] = X - 1 - xLo[i];
			xHi[i] = X - 1 - xHi[i];
		}
	}
	/* Now march over the output table generating the new values. */
	double scaleY = cameraMode.sensorHeight /
			(cameraMode.height * cameraMode.scaleY);
	double yOff = cameraMode.cropY / (double)cameraMode.sensorHeight;
	double y = .5 / scaleY + yOff * Y - .5;
	double yInc = 1 / scaleY;
	for (int j = 0; j < Y; j++, y += yInc) {
		int yLo = floor(y);
		double yf = y - yLo;
		int yHi = std::min(yLo + 1, Y - 1);
		yLo = std::max(yLo, 0);
		if (!!(cameraMode.transform & libcamera::Transform::VFlip)) {
			yLo = Y - 1 - yLo;
			yHi = Y - 1 - yHi;
		}
		double const *rowAbove = calTableIn.ptr() + X * yLo;
		double const *rowBelow = calTableIn.ptr() + X * yHi;
		double *out = calTableOut.ptr() + X * j;
		for (int i = 0; i < X; i++) {
			double above = rowAbove[xLo[i]] * (1 - xf[i]) +
				       rowAbove[xHi[i]] * xf[i];
			double below = rowBelow[xLo[i]] * (1 - xf[i]) +
				       rowBelow[xHi[i]] * xf[i];
			*(out++) = above * (1 - yf) + below * yf;
		}
	}
}

/* Calculate chrominance statistics (R/G and B/G) for each region. */
static void calculateCrCb(const RgbyRegions &awbRegion, Array2D<double> &cr,
			  Array2D<double> &cb, uint32_t minCount, uint16_t minG)
{
	for (unsigned int i = 0; i < cr.size(); i++) {
		auto s = awbRegion.get(i);

		/* Do not return unreliable, or zero, colour ratio statistics. */
		if (s.counted <= minCount || s.val.gSum / s.counted <= minG ||
		    s.val.rSum / s.counted <= minG || s.val.bSum / s.counted <= minG) {
			cr[i] = cb[i] = InsufficientData;
			continue;
		}

		cr[i] = s.val.rSum / (double)s.val.gSum;
		cb[i] = s.val.bSum / (double)s.val.gSum;
	}
}

static void applyCalTable(const Array2D<double> &calTable, Array2D<double> &C)
{
	for (unsigned int i = 0; i < C.size(); i++)
		if (C[i] != InsufficientData)
			C[i] *= calTable[i];
}

void compensateLambdasForCal(const Array2D<double> &calTable,
			     const Array2D<double> &oldLambdas,
			     Array2D<double> &newLambdas)
{
	double minNewLambda = std::numeric_limits<double>::max();
	for (unsigned int i = 0; i < newLambdas.size(); i++) {
		newLambdas[i] = oldLambdas[i] * calTable[i];
		minNewLambda = std::min(minNewLambda, newLambdas[i]);
	}
	for (unsigned int i = 0; i < newLambdas.size(); i++)
		newLambdas[i] /= minNewLambda;
}

[[maybe_unused]] static void printCalTable(const Array2D<double> &C)
{
	const Size &size = C.dimensions();
	printf("table: [\n");
	for (unsigned int j = 0; j < size.height; j++) {
		for (unsigned int i = 0; i < size.width; i++) {
			printf("%5.3f", 1.0 / C[j * size.width + i]);
			if (i != size.width - 1 || j != size.height - 1)
				printf(",");
		}
		printf("\n");
	}
	printf("]\n");
}

/*
 * Compute weight out of 1.0 which reflects how similar we wish to make the
 * colours of these two regions.
 */
static double computeWeight(double Ci, double Cj, double sigma)
{
	if (Ci == InsufficientData || Cj == InsufficientData)
		return 0;
	double diff = (Ci - Cj) / sigma;
	return exp(-diff * diff / 2);
}

/* Compute all weights. */
static void computeW(const Array2D<double> &C, double sigma,
		     SparseArray<double> &W)
{
	size_t XY = C.size();
	size_t X = C.dimensions().width;

	for (unsigned int i = 0; i < XY; i++) {
		/* Start with neighbour above and go clockwise. */
		W[i][0] = i >= X ? computeWeight(C[i], C[i - X], sigma) : 0;
		W[i][1] = i % X < X - 1 ? computeWeight(C[i], C[i + 1], sigma) : 0;
		W[i][2] = i < XY - X ? computeWeight(C[i], C[i + X], sigma) : 0;
		W[i][3] = i % X ? computeWeight(C[i], C[i - 1], sigma) : 0;
	}
}

/* Compute M, the large but sparse matrix such that M * lambdas = 0. */
static void constructM(const Array2D<double> &C,
		       const SparseArray<double> &W,
		       SparseArray<double> &M)
{
	size_t XY = C.size();
	size_t X = C.dimensions().width;

	double epsilon = 0.001;
	for (unsigned int i = 0; i < XY; i++) {
		/*
		 * Note how, if C[i] == INSUFFICIENT_DATA, the weights will all
		 * be zero so the equation is still set up correctly.
		 */
		int m = !!(i >= X) + !!(i % X < X - 1) + !!(i < XY - X) +
			!!(i % X); /* total number of neighbours */
		/* we'll divide the diagonal out straight away */
		double diagonal = (epsilon + W[i][0] + W[i][1] + W[i][2] + W[i][3]) * C[i];
		M[i][0] = i >= X ? (W[i][0] * C[i - X] + epsilon / m * C[i]) / diagonal : 0;
		M[i][1] = i % X < X - 1 ? (W[i][1] * C[i + 1] + epsilon / m * C[i]) / diagonal : 0;
		M[i][2] = i < XY - X ? (W[i][2] * C[i + X] + epsilon / m * C[i]) / diagonal : 0;
		M[i][3] = i % X ? (W[i][3] * C[i - 1] + epsilon / m * C[i]) / diagonal : 0;
	}
}

/*
 * In the compute_lambda_ functions, note that the matrix coefficients for the
 * left/right neighbours are zero down the left/right edges, so we don't need
 * need to test the i value to exclude them.
 */
static double computeLambdaBottom(int i, const SparseArray<double> &M,
				  Array2D<double> &lambda)
{
	return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width] +
	       M[i][3] * lambda[i - 1];
}
static double computeLambdaBottomStart(int i, const SparseArray<double> &M,
				       Array2D<double> &lambda)
{
	return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width];
}
static double computeLambdaInterior(int i, const SparseArray<double> &M,
				    Array2D<double> &lambda)
{
	return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][1] * lambda[i + 1] +
	       M[i][2] * lambda[i + lambda.dimensions().width] + M[i][3] * lambda[i - 1];
}
static double computeLambdaTop(int i, const SparseArray<double> &M,
			       Array2D<double> &lambda)
{
	return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][1] * lambda[i + 1] +
	       M[i][3] * lambda[i - 1];
}
static double computeLambdaTopEnd(int i, const SparseArray<double> &M,
				  Array2D<double> &lambda)
{
	return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][3] * lambda[i - 1];
}

/* Gauss-Seidel iteration with over-relaxation. */
static double gaussSeidel2Sor(const SparseArray<double> &M, double omega,
			      Array2D<double> &lambda, double lambdaBound)
{
	int XY = lambda.size();
	int X = lambda.dimensions().width;
	const double min = 1 - lambdaBound, max = 1 + lambdaBound;
	Array2D<double> oldLambda = lambda;
	int i;
	lambda[0] = computeLambdaBottomStart(0, M, lambda);
	lambda[0] = std::clamp(lambda[0], min, max);
	for (i = 1; i < X; i++) {
		lambda[i] = computeLambdaBottom(i, M, lambda);
		lambda[i] = std::clamp(lambda[i], min, max);
	}
	for (; i < XY - X; i++) {
		lambda[i] = computeLambdaInterior(i, M, lambda);
		lambda[i] = std::clamp(lambda[i], min, max);
	}
	for (; i < XY - 1; i++) {
		lambda[i] = computeLambdaTop(i, M, lambda);
		lambda[i] = std::clamp(lambda[i], min, max);
	}
	lambda[i] = computeLambdaTopEnd(i, M, lambda);
	lambda[i] = std::clamp(lambda[i], min, max);
	/*
	 * Also solve the system from bottom to top, to help spread the updates
	 * better.
	 */
	lambda[i] = computeLambdaTopEnd(i, M, lambda);
	lambda[i] = std::clamp(lambda[i], min, max);
	for (i = XY - 2; i >= XY - X; i--) {
		lambda[i] = computeLambdaTop(i, M, lambda);
		lambda[i] = std::clamp(lambda[i], min, max);
	}
	for (; i >= X; i--) {
		lambda[i] = computeLambdaInterior(i, M, lambda);
		lambda[i] = std::clamp(lambda[i], min, max);
	}
	for (; i >= 1; i--) {
		lambda[i] = computeLambdaBottom(i, M, lambda);
		lambda[i] = std::clamp(lambda[i], min, max);
	}
	lambda[0] = computeLambdaBottomStart(0, M, lambda);